Fellowship · Cohort 1
Build Production-Grade AI Systems Independently
Built for ambitious IIT, NIT, and top-tier engineering students—an intensive mentorship program focused on practical AI system development, computer vision, vector search, and real-world engineering workflows.
Build Real AI Systems. Think Like an Engineer.
- 8 Week Mentorship
- Independent Project Ownership
- AI Engineering Focused
- Internship Preparation
AI pipelines
Ingest → process → serve
Computer vision
Image & video signals
Embeddings & search
Vectors & retrieval
What you ship
End-to-end AI system
Program shape
8-week mentorship arc
Upcoming · Cohort 2
Agentic AI & Multi-Agent Systems
- Learn practical AI system development
- Build autonomous AI agents
- Design multi-agent collaboration workflows
- Integrate LLMs with APIs, databases, and tools
- Develop production-grade AI applications
- Understand orchestration, memory, planning, and execution flows
- Deploy scalable AI systems with modern architecture patterns
What This Program Offers
High-level outcomes—detailed project architecture is shared only with admitted fellows after registration.
Students will
- Work on a real-world AI engineering project
- Build systems independently
- Learn modern engineering workflows
- Understand practical AI architectures
- Gain hands-on development experience
- Prepare for internship interviews
Mentorship includes
- Architecture guidance
- Engineering reviews
- Debugging direction
- Workflow mentorship
- Technical evaluation
Skills You Will Build
A curated stack of capabilities aligned with how serious AI products are built today.
LLMs & applications
- LLM APIs & model choice
- Prompt engineering & evals
- Context, tokens & safety basics
- Tool calling & structured outputs
- RAG & grounding patterns
Agentic & multi-agent
- Autonomous agent loops
- Multi-agent collaboration
- Orchestration & planning
- Memory, state & long-running tasks
- Guardrails in production
Multimodal & retrieval
- Embeddings & vector search
- Semantic retrieval
- Computer vision signals
- Ingestion & AI pipelines
Software & craft
- APIs & backend architecture
- Deployment & observability
- GitHub workflows & debugging
- System design & technical communication
- Interview-ready narratives
Technology Stack
High-level toolkit—implementation specifics stay inside the fellow workspace.
Program Structure
Eight weeks, progressively deeper—descriptions stay conceptual on the public page.
- Week 1
Foundations & System Thinking
Problem framing and architecture mindset.
- Week 2
AI Processing Pipelines
End-to-end data flow at a high level.
- Week 3
Computer Vision Systems
Models, inputs, and evaluation loops.
- Week 4
Embeddings & Retrieval
Semantic representations and indexing concepts.
- Week 5
Intelligent Search Systems
Querying and ranking in practice.
- Week 6
AI Workflow Integration
Connecting services into a coherent product.
- Week 7
Optimization & Deployment
Performance, packaging, and rollout.
- Week 8
Final Demo & Evaluation
Presentation and technical assessment.
Who Should Apply
Ideal fellows
- · IIT, NIT, and other top-tier engineering students
- · CSE / AI / ML students
- · Students preparing for internships
- · Students interested in real AI systems
- · Builders and problem solvers
Requirements
- · Basic Python knowledge
- · Willingness to learn
- · Consistency and ownership mindset
This is NOT a tutorial-based bootcamp.
Students are expected to
- · Build independently
- · Solve problems independently
- · Maintain project consistency
- · Debug and research actively
Mentor provides
- · Guidance
- · Architecture reviews
- · Feedback
- · Engineering mentorship
Flagship AI System Project
Public teaser only—full architecture unlocks for approved accounts.
What fellows build (overview)
Students independently build an advanced AI-powered system involving:
- ◆ Intelligent video understanding
- ◆ Semantic search
- ◆ Face and object intelligence
- ◆ Embeddings and vector retrieval
- ◆ Automated indexing pipelines
Detailed project architecture available after registration approval.